A second highly selected gene, LYST, is associated with pigmentation, and changes in it are probably responsible for the blanching of the ancestors’ brown fur. Computer analysis for the multiple mutations of the gene showed that they too were almost certainly damaging to its function.

I am hoping that some members here are familiar with Bayes’ Theorem and willing to share their knowledge or at the very least interested enough in the topic to do some research and share their opinions.

– What is Bayes Theorem
– What can it tell us
– How does it work
– Can Bayes’ Theorem be abused and if so how

Darwin’s conforming of his theory to the old vera causa ideal shows that the theory of natural selection is probabilistic not because it introduces a probabilistic law or principle, but because it invokes a probabilistic cause, natural selection, definable as nonfortuitous differential reproduction of hereditary variants.

There is a pretty interesting discussion going on in Noyau regarding the many definitions of “fitness” in evolutionary biology. It would be a shame for it to be lost in that particular venue here at TSZ. At the risk of being censored by the admins for posting too many OPs in one month I thought I’d start this thread.

Here’s my take so far:

Allan Miller was charged by phoodoo with resorting to different definitions of fitness. Allan denied the charge and when asked for a definition of fitness Allan provided one. Allan later stated that his definition only properly applied to asexual species.

Others chimed in to say that the definition of fitness depends on the context, which hardly seems to contradict what phoodoo was saying.

My own position is that fitness has its definition within a particular mathematical framework. My position is also that fitness can be defined generically but that such a definition is tautological. Special definitions of fitness are required to make the concept testable.

I received my copy of Theistic Evolution today. The book contains three chapters dedicated to skepticism of universal common ancestry. As common descent seems to be a hot topic here lately I thought I’d read those chapters first and offer comments and invite responses.

I’ll start with Chapter 12, authored by Paul Nelson, which carries the title: Five Questions Everyone Should Ask about Common Descent. The five questions are as follows:

1. If species were not connected by common descent, how would we know it?
2. What were the actual transformation pathways, satisfying the continuity rule, which connect all organisms to LUCA?
3. Have we genuinely tested UCD, or merely assumed its truth?
4. When explaining the history of life, have we assumed methodological naturalism only, or have we allowed for the possibility of intelligent design?
5. In the light of intelligent design as a causal possibility, what histories for life on earth might be the case?

As usual, I don’t expect anyone else here to actually read this book because, you know, it just isn’t skeptical enough.

Because evolution proves that God does not exist. Except when it doesn’t.

In June 2004, the science historian Frank Sulloway and I began a month-long expedition to retrace Charles Darwin’s footsteps in the Galápagos Islands. It turned out to be one of the most physically grueling experiences of my life…

High-level debates in evolutionary biology often treat the Modern Synthesis as a framework of population genetics, or as an intellectual lineage with a changing distribution of beliefs. Unfortunately, these flexible notions, used to negotiate decades of innovations, are now thoroughly detached from their historical roots in the original Modern Synthesis (OMS), a falsifiable scientific theory.

of the Existence of God

Philosopher Edward Feser has a new book out in which he puts forth five arguments for the existence of God. These are not the “Five Ways” of Aquinas so it might be refreshing to discuss one or all of these. At the very least this OP may introduce readers to arguments for the existence of God which they had previously been unaware of.

Evolution is often presented as problem-solving. Genetic algorithms are often offered as proofs of evolution’s ability to solve problems. Genetic algorithms are as search algorithms.

As one book says:

Fundamentally, all evolutionary algorithms can be viewed as search algorithms which search through a set of possible solutions looking for the best – or “fittest” – solution.

Tom has asked me to specify a problem independently from the evolutionary process. Now I have to admit that I don’t really understand what that means. But I like Tom and I have a lot of respect for him, so I want to give it my best shot and see where it takes us. I’m also hoping this will shed some light on claims about how problem-solving genetic algorithms are designed to solve a particular problem.

The book may make some “skeptics” uncomfortable, but maybe they should read it anyways.

From the book:

I have come to believe that there is something presently wrong with how we scientists think about life, its existence, its origins, and its evolution.

Without a coherent theory of life, whatever we think about life doesn’t hold water. This applies to the major contribution we claim that the modern science of life offers to the popular culture: Darwinism.

… there sits at the heart of modern Darwinism an unresolved tautology that undermines its validity.

… do we have a coherent theory of evolution? The firmly settled answer to this question is supposed to be “yes” …

I intend to argue in this book that the answer to my question might actually be “no.”

Coevolutionary algorithms approach problems for which no function for evaluating potential solutions is present or known. Instead, algorithms rely on the aggregation of outcomes from interactions among evolving entities in order to make selection decisions. Given the lack of an explicit yardstick, understanding the dynamics of coevolutionary algorithms, judging whether a given algorithm is progressing, and designing effective new algorithms present unique challenges unlike those faced by optimization or evolutionary algorithms. The purpose of this chapter is to provide a foundational understanding of coevolutionary algorithms and to highlight critical theoretical and empirical work done over the last two decades. This chapter outlines the ends and means of coevolutionary algorithms: what they are meant to find, and how they should find it.

Glen: The real question is if Mung has read and comprehended Losos’ book.

keiths: Yes, which brings to mind what happened with Andreas Wagner’s book, Arrival of the Fittest. Mung was blathering about how it was an ID-friendly book, which is nonsense.

keiths:

I challenged him:

Mung,

Alan’s review barely touches on what I think are the most important ideas in the book: those concerning the “libraries”, the “networks”, and the extent to which the networks extend across the libraries.

How about summarizing those ideas for us in your own words? That will serve the dual purpose of 1) filling a gap in Alan’s review and 2) demonstrating that you actually understand what Wagner is saying.

Having summarized those ideas, if you still don’t (or pretend not to) understand the implications for ID, I’ll help you out.

And:

Think of it as being similar to an ideological Turing test. I’d like to see if you even bothered, or were able, to understand the book before dismissing it as no threat to ID.

keiths: To no one’s surprise, Mung squirmed, stalled, and then skedaddled.

I love books like this. Pure wonder about the living world. The beauty. The mystery. Shattering the myths of Darwinism while still clinging desperately to them.

We learn that Darwinism has retarded evolutionary thought for at least a century because the picture that Darwin gave us (which his disciples followed for over a hundred years) was false. Evolution can be tested. It can be observed within human lifetimes. It doesn’t require the infinitesimal insensible aggregations over millenia previously thought. Evolution can be really really fast. Which ought to be good news for young earth creationists.

We also learn that the oft-heard claim that degree of similarity implies degree of relatedness is false. That some species A looks very much like some species B doesn’t at all mean that they are more closely related than some other species which is visibly different.